Unlike other commercial treatment planning systems (TPS) which model the rounded leaf end differently (such as the MLC dosimetric leaf gap (DLG) or rounded leaf‐tip radius), the RayStation TPS (RaySearch Laboratories, Stockholm, Sweden) models transmission through the rounded leaf end of the MLC with a step function, in which the radiation transmission through the leaf end is the square root of the average MLC transmission factor. We report on the optimization of MLC model parameters for the RayStation planning system. This (TPS) models the rounded leaf end of the MLC with the following parameters: leaf‐tip offset, leaf‐tip width, average transmission factor, and tongue and groove. We optimized the MLC model parameters for IMRT in the RayStation v. 4.0 planning system and for a Varian C‐series linac with a 120‐leaf Millennium MLC, and validated the model using measured data. The leaf‐tip offset is the geometric offset due to the rounded leaf‐end design and resulting divergence of the light/radiation field. The offset value is a function of the leaf‐tip position, and tabulated data are available from the vendor. The leaf‐tip width was iteratively evaluated by comparing computed and measured transverse dose profiles of MLC defined fields at dmax in water. In‐water profile comparisons were also used to verify the MLC leaf position (leaf‐tip offset). The average transmission factor and leaf tongue‐and‐groove width were derived iteratively by maximizing the agreement between measurements and RayStation TPS calculations for five clinical IMRT QA plans. Plan verifications were performed by comparing MapCHECK2 measurements and Monte Carlo calculations. The MLC model was validated using five test IMRT cases from the AAPM Task Group 119 report. Absolute gamma analyses (3 mm/3% and 2 mm/2%) were applied. In addition, computed output factors for MLC‐defined small fields (2×2,3×3,4×4,6×6 cm2) of both 6 MV and 18 MV photons were compared to those independently measured by the Imaging and Radiation Oncology Core (IROC), Houston, TX. 6 MV and 18 MV models were both determined to have the same MLC parameters: leaf‐tip offset=0.3 cm,2.5% transmission, and leaf tongue‐and‐groove width=0.05 cm. IMRT QA analysis for five test cases in TG‐119 resulted in a 100% passing rate with 3 mm/3% gamma analysis for 6 MV, and >97.5% for 18 MV. The passing rate was >94.6% for 6 MV and >90.9% for 18 MV when the 2 mm/2% gamma analysis criteria was applied. These results compared favorably with those published in AAPM Task Group 119. The reported MLC model parameters serve as a reference for other users.PACS number(s): 87.55.D, 87.56.nk
This study introduces a practical four-dimensional (4D) planning scheme of IMAT using 4D computed tomography (4D CT) for planning tumor tracking with dynamic multileaf beam collimation. We assume that patients can breathe regularly, i.e., the same way as during 4D CT with an unchanged period and amplitude, and that the start of 4D-IMAT delivery can be synchronized with a designated respiratory phase. Each control point of the IMAT-delivery process can be associated with an image set of 4D CT at a specified respiratory phase. Target is contoured at each respiratory phase without a motion-induced margin. A 3D-IMAT plan is first optimized on a reference-phase image set of 4D CT. Then, based on the projections of the planning target volume (PTV) in the beam’s eye view (BEV) at different respiratory phases, a 4D-IMAT plan is generated by transforming the segments of the optimized 3D plan by using a direct aperture deformation (DAD) method. Compensation for both translational and deformable tumor motion is accomplished, and the smooth delivery of the transformed plan is ensured by forcing connectivity between adjacent angles (control points). It is envisioned that the resultant plans can be delivered accurately using the dose rate regulated tracking (DRRT) method which handles breathing irregularities (Yi et al 2008). This planning process is straightforward and only adds a small step to current clinical 3D planning practice. Our 4D planning scheme was tested on three cases to evaluate dosimetric benefits. The created 4D-IMAT plans showed similar dose distributions as compared with the 3D-IMAT plans on a single static phase, indicating that our method is capable of eliminating the dosimetric effects of breathing induced target motion. Compared to the 3D-IMAT plans with large treatment margins encompassing respiratory motion, our 4D-IMAT plans reduced radiation doses to surrounding normal organs and tissues.
Purpose: Dose-rate-regulated tracking (DRRT) is a tumor tracking strategy that programs the MLC to track the tumor under regular breathing and adapts to breathing irregularities during delivery using dose rate regulation. Constant-dose-rate tracking (CDRT) is a strategy that dynamically repositions the beam to account for intrafractional 3D target motion according to real-time information of target location obtained from an independent position monitoring system. The purpose of this study is to illustrate the differences in the effectiveness and delivery accuracy between these two tracking methods in the presence of breathing irregularities. Methods:Step-and-shoot IMRT plans optimized at a reference phase were extended to remaining phases to generate 10-phased 4D-IMRT plans using segment aperture morphing (SAM) algorithm, where both tumor displacement and deformation were considered. A SAM-based 4D plan has been demonstrated to provide better plan quality than plans not considering target deformation. However, delivering such a plan requires preprogramming of the MLC aperture sequence. Deliveries of the 4D plans using DRRT and CDRT tracking approaches were simulated assuming the breathing period is either shorter or longer than the planning day, for 4 IMRT cases: two lung and two pancreatic cases with maximum GTV centroid motion greater than 1 cm were selected. In DRRT, dose rate was regulated to speed up or slow down delivery as needed such that each planned segment is delivered at the planned breathing phase. In CDRT, MLC is separately controlled to follow the tumor motion, but dose rate was kept constant. In addition to breathing period change, effect of breathing amplitude variation on target and critical tissue dose distribution is also evaluated. Results: Delivery of preprogrammed 4D plans by the CDRT method resulted in an average of 5% increase in target dose and noticeable increase in organs at risk (OAR) dose when patient breathing is either 10% faster or slower than the planning day. In contrast, DRRT method showed less than 1% reduction in target dose and no noticeable change in OAR dose under the same breathing period irregularities. When ±20% variation of target motion amplitude was present as breathing irregularity, the two delivery methods show compatible plan quality if the dose distribution of CDRT delivery is renormalized. Conclusions: Delivery of 4D-IMRT treatment plans, stemmed from 3D step-and-shoot IMRT and preprogrammed using SAM algorithm, is simulated for two dynamic MLC-based real-time tumor tracking strategies: with and without dose-rate regulation. Comparison of cumulative dose distribution indicates that the preprogrammed 4D plan is more accurately and efficiently conformed using the DRRT strategy, as it compensates the interplay between patient breathing irregularity and tracking delivery without compromising the segment-weight modulation.
Purpose: To commission electron Monte Carlo (eMC) algorithm in Eclipse Treatment Planning System (TPS) for TrueBeam Linacs, including the evaluation of dose calculation accuracy for small fields and oblique beams and comparison with the existing eMC model for Clinacs. Methods: Electron beam percent‐depth‐dose (PDDs) and profiles with and without applicators, as well as output factors, were measured from two Varian TrueBeam machines. Measured data were compared against the Varian TrueBeam Representative Beam Data (VTBRBD). The selected data set was transferred into Eclipse for beam configuration. Dose calculation accuracy from eMC was evaluated for open fields, small cut‐out fields, and oblique beams at different incident angles. The TrueBeam data was compared to the existing Clinac data and eMC model to evaluate the differences among Linac types. Results: Our measured data indicated that electron beam PDDs from our TrueBeam machines are well matched to those from our Varian Clinac machines, but in‐air profiles, cone factors and open‐filed output factors are significantly different. The data from our two TrueBeam machines were well represented by the VTBRBD. Variations of TrueBeam PDDs and profiles were within the 2% /2mm criteria for all energies, and the output factors for fields with and without applicators all agree within 2%. Obliquity factor for two clinically relevant applicator sizes (10×10 and 15×15 cm^2) and three oblique angles (15, 30, and 45 degree) were measured for nominal R100, R90, and R80 of each electron beam energy. Comparisons of calculations using eMC of obliquity factors and cut‐out factors versus measurements will be presented. Conclusion: eMC algorithm in Eclipse TPS can be configured using the VTBRBD. Significant differences between TrueBeam and Clinacs were found in in‐air profiles and open field output factors. The accuracy of the eMC algorithm was evaluated for a wide range of cut‐out factors and oblique incidence.
Purpose: We developed an algorithm to minimize total inter‐segment time (TIST) for the MLC‐based real‐time tumor tracking with step‐and‐shoot IMRT. This algorithm optimizes a starting phase of tumor motion for each segment to minimize TIST. Methods: The optimizing algorithm consists of four steps: (1) implementation of feathering motion for the closed leaves that will be opened at the next segment, (2) calculation of inter‐segment time for all segments, (3) reordering segments to minimize TIST, and (4) optimization of the starting phase of tumor motion for each segment to minimize TIST. Thirty step‐and‐shoot IMRT fields from five patients with lung and abdominal cancer were used to test the algorithm. Tumor motion was varied with a period (2.0 to 4.0 s) and a peak‐to‐peak distance (0.5 to 4.0 cm). TIST and duty cycle for each field were compared to those from the strategy of starting each segment at end‐of‐exhale. Results: The TIST was reduced by 54.0% on average (from 30.2 ± 16.9 to 13.9 ± 10.6 s) and, the effective duty cycle was increased from 32 ± 10% to 52 ± 15% for a tumor motion with 4 s and 1.0 cm peak‐to‐peak. More reduction in the TIST was observed from 45.1 to 72.1% with an increase of the period from 2 to 8 s; effect of reduction was degraded by 54.5 to 46.2% when the peak‐to‐peak increased from 0.5 to 4.0 cm. The TIST increased when a field size formed by x‐jaws increased (correlation coefficient: 0.7). Conclusions: : Total treatment time was reduced noticeably with the algorithm presented in this study so that real‐time tumor tracking can be delivered with step‐and‐shoot IMRT with an increased duty cycle. This research was supported in part by a NIH grant 1R01CA133539‐01A2 and in part by the Intramural Research Program of the NIH, NCI.
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